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Understanding factors that enhance participants' satisfaction has become critical to developing effective donor retention strategies for charity sport events (CSEs). However, there is a lack of empirical research on participants' satisfaction with CSEs. The purpose of this study is to examine the antecedents and consequences of satisfaction among CSE participants and to empirically test the relationships between the proposed constructs.

Data were collected from 238 participants from four Relay For Life (RFL) events organized by the American Cancer Society, North Central Region in the USA. Confirmatory factor analysis and structural equation modeling were conducted to analyze the measurement model and the structural model.

The results of the structural model indicated that perceived prosocial impact, sense of community and trust in CSE had significant positive effects on CSE satisfaction, while venue quality, knowledge attainment and entertainment value did not positively influence CSE satisfaction. CSE satisfaction had a positive direct effect on participant loyalty to CSE, which had a significant contribution to future participant intent.

The findings of this study provide CSE directors and marketers with valuable insights into the process of how to build long-term relationships with participants by identifying factors that influence participants' satisfaction and its consequences.

By measuring the mediating role of CSE satisfaction, this study provides a deeper understanding of the causal pathways from the antecedents to participant loyalty through CSE satisfaction.

Privacy considerations have become a topic with increasing interest from academics, industry leaders and regulators. In response to consumers’ privacy concerns, Google announced in 2020 that Chrome would stop supporting third-party cookies in the near future. At the same time, advertising technology companies are developing alternative solutions for online targeting and consumer privacy controls. This paper aims to explore privacy considerations related to online tracking and targeting methods used for programmatic advertising (i.e. third-party cookies, Privacy Sandbox, Unified ID 2.0) for a variety of stakeholders: consumers, AdTech platforms, advertisers and publishers.

This study analyzes the topic of internet user privacy concerns, through a multi-pronged approach: industry conversations to collect information, a comprehensive review of trade publications and extensive empirical analysis. This study uses two methods to collect data on consumer preferences for privacy controls: a survey of a representative sample of US consumers and field data from conversations on web-forums created by tech professionals.

The results suggest that there are four main segments in the US internet user population. The first segment, consisting of 26% of internet users, is driven by a strong preference for relevant ads and includes consumers who accept the premises of both Privacy Sandbox and Unified ID (UID) 2.0. The second segment (26%) includes consumers who are ambivalent about both sets of premises. The third segment (34%) is driven by a need for relevant ads and a strong desire to prevent advertisers from aggressively collecting data, with consumers who accept the premises of Privacy Sandbox but reject the premises of UID 2.0. The fourth segment (15% of consumers) rejected both sets of premises about privacy control. Text analysis results suggest that the conversation around UID 2.0 is still nascent. Google Sandbox associations seem nominally positive, with sarcasm being an important factor in the sentiment analysis results.

The value of this paper lies in its multi-method examination of online privacy concerns in light of the recent regulatory legislation (i.e. General Data Protection Regulation and California Consumer Privacy Act) and changes for third-party cookies in browsers such as Firefox, Safari and Chrome. Two alternatives proposed to replace third-party cookies (Privacy Sandbox and Unified ID 2.0) are in the proposal and prototype stage. The elimination of third-party cookies will affect stakeholders, including different types of players in the AdTech industry and internet users. This paper analyzes how two alternative proposals for privacy control align with the interests of several stakeholders.

The purpose of this paper is to understand knowledge grafting through localized professionals in the internationalization of the firm. Knowledge grafting refers to firms increasing their knowledge stock by acquiring new staff, and while the concept is not new in studies on firms’ internationalization, there is little understanding of the characteristics of the individuals carrying the knowledge, the types of knowledge grafted and how it contributes to a market entry process.

The authors conducted an explorative study with a multiple-case research design and purposely selected five localized Swedish managers working for Russian subsidiaries of Swedish firms. Face-to-face interviews were conducted. The interviews were transcribed and analyzed based on three types of knowledge: general foreign market knowledge, social network knowledge and professional knowledge. The authors also considered both private and professional ties.

The findings show that characteristics of the localized professional and the firm can influence the type of knowledge grafted and how it is used. The findings also highlight the key role of the individual as knowledge carrier and show an alternative way to obtain knowledge in firm internationalization.

This study comes with limitations. Only Swedish firms entering Russia with wholly owned subsidiaries have been considered. Further studies comparing knowledge grafting with firms in different entry mode, varying stage of market entry, as well as other countries of origin can further enrich our understanding. Future studies can also focus on localized professionals to shed light on the knowledge transfer between them and other individuals within the firms and the potential impact of their departure on knowledge grafting.

Internationalizing firms should pay attention to the opportunity of grafting knowledge by appointing localized professionals already living in the market. Governmental agencies in the host county can be a valuable source for identifying foreign nationals of the same origin as the firm.

To the best of the authors’ knowledge, this is the first study to focus on the individual level of knowledge grafting and to examine how localized professionals acquire knowledge to support firms in internationalization.

Dr. Anna Julia Cooper was an early, radical educational pioneer who asked why African Americans were perceived as problematic to society and subjected to economic biases (Berry, 2006; May, 2007) Her life spanned the period of the Civil War to the dawn of the Civil Rights Movement ,. Reflecting on the Dred Scott decision of 1850 further solidified Cooper’s mindset about dominant, powerful Caucasian men. Cooper’s economic views are examined through legislation continuously tolerating African Americans as economic property for profit, the underemployment of African-American women, women as economically oppressed, and the institutionalization of racism in churches and education which contributed to the success of industry.

The purpose of this paper is to investigate the relationships between some aspect‐oriented metrics and aspect fault proneness, content and fixing effort.

An exploratory case study was conducted using an open source aspect‐oriented software consisting of 76 aspects, and 13 aspect‐oriented metrics were investigated that measure different structural properties of an aspect: size, coupling, cohesion, and inheritance. In addition, different prediction models for aspect fault proneness, content and fixing effort were built using different combinations of metrics' categories.

The results obtained from this study indicate statistically significant correlation between most of the size metrics and aspect fault proneness, content and fixing effort. The cohesion metric was also found to be significantly correlated with the same. Moreover, it was observed that the best accuracy in aspect fault proneness, content and fixing effort prediction can be achieved as a function of some size metrics.

Fault prediction helps software developers to focus their quality assurance activities and to allocate the needed resources for these activities more effectively and efficiently; thus improving software reliability. In literature, some aspect‐oriented metrics have been evaluated for aspect fault proneness prediction, but not for other fault‐related prediction problems such as aspect fault content and fixing effort.

EVERYONE interested in the British library movement will learn with sorrow and regret that one of its greatest friends and strongest champions has passed away, in the person of Thomas Greenwood, the kind‐hearted and generous advocate of libraries, who won the respect and regard of every English libiarian. From one of his own periodicals the following particulars are abstracted:—

This paper aims to describe several artificial intelligence (AI)-based applications that librarians can use to serve and design virtual library instruction, so it will be more effective and efficient.

The approach involves a comprehensive review of AI-based applications that bring benefits to librarian to enhance the virtual instructional services (AI). This study explores the existing papers to reveal the potential use of AI for research consultation, designing the instructional services and conducting evaluation of the program.

There are some AI-based applications that are available for free that will help instructional librarian jobs. Librarians use the AI to increase effectiveness of the services. The AI-based applications that can be used to support instructional services on research inquiries include virtual assistance, knowledge mapping and note making, and to support designing virtual instruction, librarians can use design apps, image generators, voice generator, grammar checker and paraphrasing.

There are many studies on AI at the library; however, it’s still rare a paper studied AI-based application that potentially will bring benefit for virtual instructional services. This paper will give overview of AI application that will help instructional librarian on transactions with users and help librarians to create innovative instructional media.

The purpose of this study is to investigate the physical, chemical and thermal characteristics of paraffin-blended fuels to determine their suitability as fuel in hybrid rockets.

Wax fuels are viable and efficient alternatives to conventional rocket fuels, having excellent structural strength and thermal and mechanical properties. The authors report a study of the morphological, chemical and thermal properties of paraffin wax with and without additives for use as fuels in hybrid rockets. Scanning electron microscopy, X-ray diffraction and Fourier transform infrared spectroscopy were used for the morphological and chemical characterizations of the fuel blends. The thermal stability and combustion characteristics were assessed under an atmosphere of nitrogen by the simultaneous application of thermogravimetry and differential scanning calorimetry techniques.

The melting temperatures for pure paraffin and other formulations were around 61°C as seen in differential scanning calorimetry experiments. Variations in the compositions of monoesters, n-alkanes, fatty acids, carboxylic acids methyl and hydroxyl esters in the fuel samples were assessed using Fourier transform infrared spectroscopy. The assessment criterion was chosen as the relative content of carbonyl groups, and the ratio of the stretching vibration of the C–C bonds to the deformation vibration of the aliphatic carbon–hydrogen bonds was taken as the basis for the quantitative calibration. The crystal phases identified by X-ray diffraction were used to identify nonlinear chemicals and alkane lengths. Scanning electron microscopy validated homogeneity in the paraffin-blended samples.

This study presents the thermal stability and other relevant characteristics of fuel formulations comprising unconventional blends.

The purpose of this study is to explore to which extent data mining research would be associated with the library and information science (LIS) discipline. This study aims to identify data mining related subject terms and topics in representative LIS scholarly publications.

A large set of bibliographic records over 38,000 was collected from a scholarly database representing the fields of LIS and the data mining, respectively. A multitude of text mining techniques were applied to investigate prevailing subject terms and research topics, such as influential term analysis and Dirichlet multinomial regression topic modeling.

The findings of this study revealed the relationship between the LIS and data mining research domains. Various data mining method terms were observed in recent LIS publications, such as machine learning, artificial intelligence and neural networks. The topic modeling result identified prevailing data mining related research topics in LIS, such as machine learning, deep learning, big data and among others. In addition, this study investigated the trends of popular topics in LIS over time in the recent decade.

This investigation is one of a few studies that empirically investigated the relationships between the LIS and data mining research domains. Multiple text mining techniques were employed to delineate to which extent the two research domains would be associated with each other based on both at the term-level and topic-level analysis. Methodologically, the study identified influential terms in each domain using multiple feature selection indices. In addition, Dirichlet multinomial regression was applied to explore LIS topics in relation to data mining.

The purpose of this paper is to analyse the publication of big data in the library from Scopus database by looking at the writing time period of the papers, author's country, the most frequently occurring keywords, the article theme, the journal publisher and the group of keywords in the big data article. The methodology used in this study is a quantitative approach by extracting data from Scopus database publications with the keywords “big data” and “library” in May 2019. The collected data was analysed using Voxviewer software to show the keywords or terms. The results of the study stated that articles on big data have appeared since 2012 and are increasing in number every year. The big data authors are mostly from China and America. Keywords that often appear are based on the results of terminology visualization are including, “big data”, “libraries”, “library”, “data handling”, “data mining”, “university libraries”, “digital libraries”, “academic libraries”, “big data applications” and “data management”. It can be concluded that the number of publications related to big data in the library is still small; there are still many gaps that need to be researched on the topic. The results of the research can be used by libraries in using big data for the development of library innovation.

The Scopus database was accessed on 24 May 2019 by using the keyword “big data” and “library” in the search box. The authors only include papers, which title contain of big data in library. There were 74 papers, however, 1 article was dropped because of it not meeting the criteria (affiliation and abstract were not available). The papers consist of journal articles, conference papers, book chapters, editorial and review. Then the data were extracted into excel and analysed as follows (by the year, by the author/s’s country, by the theme and by the publisher). Following that the collected data were analysed using VOX viewer software to see the relationship between big data terminology and library, terminology clustering, keywords that often appear, countries that publish big data, number of big data authors, year of publication and name of journals that publish big data and library articles (Alagu and Thanuskodi, 2019).

It can be concluded that the implementation of big data in libraries is still in an early stage, it is shown from the limited number of practical implementation of big data analytics in library. Not many libraries that use big data to support innovation and services since there were lack of librarian skills of big data analytics. The library manager’s view of big data is still not necessary to do. It is suggested for academic libraries to start their adoption of big data analytics to support library services especially research data. To do so, librarians can enhance their skills and knowledge by following some training in big data analytics or research data management. The information technology infrastructure also needs to be upgraded since big data need big IT capacity. Finally, the big data management policy should be made to ensure the implementation goes well.

This paper discovers the adoption and implementation of big data in library, many papers talk big data in business and technology context. This is offering new idea for many libraries especially academic library about the adoption of big data to support their services. They can adopt the big data analytics technology and technique that suitable for their library.